# Fly.io deployment example

This project modifies the `bot_runner.py` server to launch a new machine for each user session. This is a recommended approach for production vs. running shell processess as your deployment will quickly run out of system resources under load.

For this example, we are using Daily as a WebRTC transport and provisioning a new room and token for each session. You can use another transport, such as WebSockets, by modifying the `bot.py` and `bot_runner.py` files accordingly.

## Setting up your fly.io deployment

### Create your fly.toml file

You can copy the `example-fly.toml` as a reference. Be sure to change the app name to something unique.

### Create your .env file

Copy the base `env.example` to `.env` and enter the necessary API keys.

`FLY_APP_NAME` should match that in the `fly.toml` file.

### Launch a new fly.io project

`fly launch` or `fly launch --org your-org-name`

### Set the necessary app secrets from your .env

Note: you can do this manually via the fly.io dashboard under the "secrets" sub-section of your deployment (e.g. "https://fly.io/apps/fly-app-name/secrets") or run the following terminal command:

`cat .env | tr '\n' ' ' | xargs flyctl secrets set`

### Deploy your machine

`fly deploy`

## Connecting to your bot

Send a post request to your running fly.io instance:

`curl --location --request POST 'https://YOUR_FLY_APP_NAME/start_bot'`

This request will wait until the machine enters into a `starting` state, before returning the a room URL and token to join.